Embedded domain has witnessed the application of different code compression methodologies on different architectures to bridge the gap between ever-increasing application size and scarce memory resources.
In order to address the high demand for audio compression, over the years many compression methodologies were introduced to reduce the bit rates without sacrificing much of the audio quality.
Since it is out of scope of this paper to cover all of the existing audio compression methodologies, the authors recommend the work of Painter and Spanias in [24] for a comprehensive review of most of the existing audio compression techniques.
These included the development of practical image and video compression technology, advanced methodologies for data-rich manufacturing problems, which he pursued under the MIT Leaders for Manufacturing program, heterogeneous and wireless communication architectures, and, most recently, neuronal computation models.
This paper proposes a methodology for compression of electrical power signals from waveform records in electric systems, using genetic algorithm (GA) and artificial neural network (ANN).
Finally, numerical results on two typical cases including the single notched four-point bending model and the soil slope stability model under compression demonstrate the proposed methodology by studying the effects of the mesh size and cohesive surface energy on the evolutive localization interface and the load displacement responses.
The Swedish National Rail Administration (Banverket) carried out a research project in 2005 to evaluate the application of the UIC capacity methodology (timetable compression) for the Swedish rail network.
Additional research is required in future work to extend the scope of compressed sensing in scientific data compression and strengthen its underlying methodology.
The spherically enclosed atoms represent a model that has been applied in the analysis of several confined systems with different methodologies where compression is simulated through hard or soft walls.
The issues of rate control are important in video compression [10] and such methodologies as operational R-D theory, model-based rate control, and the Rate-Distortion Optimization (RDO) are exploited to achieve good coding performances [11, 12].
